Katabi, Dina

33 publications

CVPR 2025 Language-Guided Image Tokenization for Generation Kaiwen Zha, Lijun Yu, Alireza Fathi, David A. Ross, Cordelia Schmid, Dina Katabi, Xiuye Gu

NeurIPS 2025 RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning Kaiwen Zha, Zhengqi Gao, Maohao Shen, Zhang-Wei Hong, Duane S Boning, Dina Katabi

NeurIPS 2025 Single-Teacher View Augmentation: Boosting Knowledge Distillation via Angular Diversity Seonghoon Yu, Dongjun Nam, Dina Katabi, Jeany Son

CVPR 2024 Learning Vision from Models Rivals Learning Vision from Data Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi, Dilip Krishnan, Phillip Isola

ICLR 2024 Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan

NeurIPS 2024 Return of Unconditional Generation: A Self-Supervised Representation Generation Method Tianhong Li, Dina Katabi, Kaiming He

CVPR 2024 Scaling Laws of Synthetic Images for Model Training ... for Now Lijie Fan, Kaifeng Chen, Dilip Krishnan, Dina Katabi, Phillip Isola, Yonglong Tian

WACV 2023 Addressing Feature Suppression in Unsupervised Visual Representations Tianhong Li, Lijie Fan, Yuan Yuan, Hao He, Yonglong Tian, Rogerio Feris, Piotr Indyk, Dina Katabi

ICML 2023 Change Is Hard: A Closer Look at Subpopulation Shift Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi

MLHC 2023 Contactless Oxygen Monitoring with Radio Waves and Gated Transformer Hao He, Yuan Yuan, Ying-Cong Chen, Peng Cao, Dina Katabi

NeurIPS 2023 Improving CLIP Training with Language Rewrites Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian

ICLR 2023 Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning Hao He, Kaiwen Zha, Dina Katabi

CVPR 2023 MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis Tianhong Li, Huiwen Chang, Shlok Mishra, Han Zhang, Dina Katabi, Dilip Krishnan

NeurIPSW 2023 On Mitigating Shortcut Learning for Fair Chest X-Ray Classification Under Distribution Shift Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi

NeurIPS 2023 Rank-N-Contrast: Learning Continuous Representations for Regression Kaiwen Zha, Peng Cao, Jeany Son, Yuzhe Yang, Dina Katabi

ICLR 2023 SimPer: Simple Self-Supervised Learning of Periodic Targets Yuzhe Yang, Xin Liu, Jiang Wu, Silviu Borac, Dina Katabi, Ming-Zher Poh, Daniel McDuff

ICCV 2023 Unsupervised Object Localization with Representer Point Selection Yeonghwan Song, Seokwoo Jang, Dina Katabi, Jeany Son

NeurIPSW 2022 Contactless Oxygen Monitoring with Gated Transformer Hao He, Yuan Yuan, Ying-Cong Chen, Peng Cao, Dina Katabi

ECCV 2022 On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond Yuzhe Yang, Hao Wang, Dina Katabi

CVPR 2022 Targeted Supervised Contrastive Learning for Long-Tailed Recognition Tianhong Li, Peng Cao, Yuan Yuan, Lijie Fan, Yuzhe Yang, Rogerio S. Feris, Piotr Indyk, Dina Katabi

CVPR 2022 Unsupervised Domain Generalization by Learning a Bridge Across Domains Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogerio S. Feris, Leonid Karlinsky

WACV 2022 Unsupervised Learning for Human Sensing Using Radio Signals Tianhong Li, Lijie Fan, Yuan Yuan, Dina Katabi

ICML 2021 Delving into Deep Imbalanced Regression Yuzhe Yang, Kaiwen Zha, Yingcong Chen, Hao Wang, Dina Katabi

ICML 2020 Continuously Indexed Domain Adaptation Hao Wang, Hao He, Dina Katabi

ICLR 2020 Harnessing Structures for Value-Based Planning and Reinforcement Learning Yuzhe Yang, Guo Zhang, Zhi Xu, Dina Katabi

ECCV 2020 In-Home Daily-Life Captioning Using Radio Signals Lijie Fan, Tianhong Li, Yuan Yuan, Dina Katabi

ICLR 2020 Learning Compositional Koopman Operators for Model-Based Control Yunzhu Li, Hao He, Jiajun Wu, Dina Katabi, Antonio Torralba

ICLR 2020 Self-Supervised Learning of Appliance Usage Chen-Yu Hsu, Abbas Zeitoun, Guang-He Lee, Dina Katabi, Tommi Jaakkola

AAAI 2019 Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi

ICML 2019 Circuit-GNN: Graph Neural Networks for Distributed Circuit Design Guo Zhang, Hao He, Dina Katabi

ICLR 2019 Learning-Based Frequency Estimation Algorithms Chen-Yu Hsu, Piotr Indyk, Dina Katabi, Ali Vakilian

ICML 2019 ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation Yuzhe Yang, Guo Zhang, Dina Katabi, Zhi Xu

ICML 2017 Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture Mingmin Zhao, Shichao Yue, Dina Katabi, Tommi S. Jaakkola, Matt T. Bianchi